
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "4"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 93 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 89 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.127401	-0.557817	-0.897602	-0.696214	1.450618	0.590629	1.122958	0.136723	0.7276	0.7025	0.2598	10.838227	11.910580
2459593	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.032832	1.711297	-0.897985	-0.506826	1.125954	1.859345	1.497446	0.338257	0.6450	0.6180	0.2191	6.413944	6.227466
2459592	RF_maintenance	0.00%	100.00%	100.00%	0.00%	-	-	0.200185	-0.504177	-0.337707	-0.668480	-0.159398	0.211782	1.798002	-0.127997	0.0321	0.0299	0.0026	nan	nan
2459591	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.273502	3.936350	-0.918335	-0.001047	0.370316	1.359375	1.042495	-0.525154	0.5298	0.5290	0.3066	7.543334	6.827031
2459590	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.321289	4.319101	-0.977508	-0.370975	1.544838	3.187611	2.200195	0.182967	0.5346	0.5300	0.3038	7.330760	6.836374
2459589	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.045718	4.762686	-1.041469	-0.348444	0.678785	1.446430	2.350012	1.536951	0.6199	0.5895	0.2382	7.076723	6.334403
2459588	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.052671	1.883930	-0.711403	-0.622410	3.181197	3.635681	2.473697	2.003917	0.7130	0.6695	0.2143	10.637787	10.686755
2459587	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	0.226341	4.262865	-0.594812	0.585327	-0.661370	-0.596781	1.343364	-0.699866	nan	nan	nan	16.316228	16.274650
2459586	RF_maintenance	100.00%	1.08%	1.08%	0.00%	100.00%	0.00%	-0.109398	2.252723	0.311904	-0.106824	-0.127308	1.771662	4.611515	0.070448	0.5356	0.5321	0.2937	6.434139	4.666148
2459585	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	2.088203	-1.462342	1.903832	0.032214	2.273450	-0.199433	2.983103	-0.264566	0.0322	0.0319	0.0016	0.000000	0.000000
2459584	RF_maintenance	100.00%	33.61%	36.61%	0.00%	100.00%	0.00%	0.185726	6.204706	0.442114	0.180565	-0.065046	1.887514	0.264978	-0.014563	0.4799	0.4801	0.3009	12.280471	8.577033
2459583	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459582	RF_maintenance	0.00%	2.70%	6.49%	0.00%	100.00%	0.00%	0.002806	3.814832	-0.572573	-0.402819	-0.169820	1.319336	0.672598	-0.240498	0.5213	0.5187	0.3220	5.826217	4.687816
2459581	RF_maintenance	100.00%	0.00%	2.70%	0.00%	100.00%	0.00%	0.211832	5.203081	-0.159618	-0.689942	-0.159883	1.171079	1.646002	0.393579	0.5328	0.5287	0.3227	5.488624	4.592479
2459580	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.137052	3.865509	-0.740206	-0.569680	0.297020	1.913026	0.566317	1.466558	0.5395	0.5376	0.3194	7.347043	5.331627
2459579	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.187896	4.825331	-0.474286	-0.194498	0.149318	1.919662	3.691495	0.197412	0.5349	0.5330	0.3228	7.475848	5.673006
2459578	RF_maintenance	0.00%	100.00%	100.00%	0.00%	-	-	-0.406888	0.002769	-0.712624	-0.623317	-1.102465	-0.667022	-0.404196	-0.149735	0.0336	0.0302	0.0024	nan	nan
2459577	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.306825	5.071651	-0.332772	-0.589218	0.226716	0.891678	1.534376	1.409256	0.5403	0.5396	0.3189	5.278735	4.193713
2459576	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	0.111104	4.504834	-0.116718	0.088119	0.258941	-0.126079	3.882194	2.300522	0.0734	0.0565	0.0096	0.847328	0.848767
2459575	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459574	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.179410	0.067093	-0.407377	-0.469362	0.565758	-1.012120	2.917515	0.061283	0.0692	0.0601	0.0068	1.202241	1.204141
2459573	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.002958	2.560338	-0.678141	-0.670841	0.082560	1.020293	3.446828	0.249090	0.0511	0.0556	0.0036	0.000000	0.000000
2459572	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459571	RF_maintenance	0.00%	100.00%	100.00%	0.00%	-	-	-0.207285	-0.047479	-0.790002	-0.717177	-1.347235	-0.425595	-0.536705	-0.574665	0.0346	0.0335	0.0045	nan	nan
2459570	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459569	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.128045	0.637836	-0.224715	-0.496828	-0.158923	0.158370	-0.121679	-0.294399	0.0622	0.0628	0.0044	1.223873	1.223800
2459566	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.049661	3.661468	-0.204202	-0.439419	0.128201	1.093108	1.035265	-0.603915	0.0700	0.0609	0.0063	10.547562	2.089856
2459565	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	-1.019629	-1.019629	-0.885933	-0.885933	-0.752740	-0.752740	-0.803206	-0.803206	nan	nan	nan	0.000000	0.000000
2459564	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.102157	2.431915	0.145606	0.146053	-0.283768	-0.754475	1.348326	1.659769	0.6999	0.6928	0.4091	4.678668	3.559415
2459563	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459562	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459561	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459560	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459559	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.077953	1.768536	0.090064	-0.105147	-0.362955	-0.649826	0.183780	1.324100	0.6961	0.6913	0.3969	4.104007	3.270689
2459558	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.196822	2.908510	-0.770618	-0.588459	0.425373	1.951039	0.055810	3.816267	0.6976	0.6869	0.4056	6.004443	4.164010
2459557	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0353	0.0334	0.0044	nan	nan
2459556	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.326302	2.764536	-0.682006	-0.490129	0.554673	0.901441	-0.378042	1.701932	0.7006	0.6933	0.4016	5.796947	3.953326
2459553	RF_maintenance	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.7012	0.6870	0.4120	nan	nan
2459552	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.616894	3.002191	-0.471088	-0.672134	0.909316	1.618405	0.464915	4.919181	0.7082	0.6947	0.4090	5.532351	3.488667
2459551	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.011799	2.028000	0.133135	-0.075199	-0.157711	-0.424610	0.009298	-0.171331	0.7016	0.6928	0.4052	4.662283	3.508143
2459550	RF_maintenance	-	99.18%	99.18%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0459	0.0496	0.0022	nan	nan
2459549	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.062391	3.038967	-0.371276	-0.677512	1.191949	1.176908	-0.295326	0.003449	0.7011	0.6917	0.4162	5.010211	3.925532
2459542	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.003110	2.935467	0.251699	-0.616305	-0.379469	-0.220891	-0.487201	1.093458	0.7589	0.7426	0.3743	5.254645	4.053936
2459541	RF_maintenance	0.00%	1.34%	1.79%	0.00%	100.00%	0.00%	-0.003132	2.730188	-0.880589	-0.558159	-0.457023	-0.312617	0.164475	0.563664	0.7541	0.7309	0.3483	6.534436	5.595788
2459540	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459536	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.494960	7.739085	0.150771	0.437698	0.391734	-0.414724	-0.199106	2.581137	0.7272	0.7205	0.4337	6.294343	4.629584
2459535	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.218850	1.484302	-0.091991	-0.385124	-0.023562	3.470407	-0.090124	3.689629	0.7823	0.7484	0.3872	4.954311	3.652512
2459534	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.233301	1.238063	-0.149082	-0.598854	1.095988	3.277775	-0.078898	2.405668	0.7764	0.7462	0.3756	5.659246	4.490279
2459533	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.253373	2.842997	-0.841589	-0.428097	0.703708	2.921743	-0.293234	5.573500	0.7182	0.7039	0.4197	5.120852	4.146356
2459532	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.304499	3.267308	-0.678803	-0.630118	1.333557	2.636725	-0.598193	2.811112	0.7181	0.7032	0.4201	5.383752	4.453506
2459530	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.094697	1.388840	-0.002879	-0.202580	0.019835	0.530088	0.018882	3.597127	0.7371	0.7200	0.4170	5.035434	3.999588
2459527	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.164765	2.677356	-0.802938	-0.361769	1.365492	1.139298	-0.708973	1.145637	0.8928	0.9181	0.3627	0.000000	0.000000
2459523	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	0.215041	5.803863	0.091806	-0.682036	-0.637264	2.037543	0.756196	5.887933	nan	nan	nan	6.024570	4.846495
2459522	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.486283	3.933807	-0.701113	-0.655576	0.977657	3.379419	0.268663	7.611050	0.7038	0.6214	0.3966	6.169764	9.172313
2459513	RF_maintenance	0.00%	100.00%	100.00%	0.00%	-	-	-0.141714	-0.008214	-0.621624	-0.805065	-0.742455	-0.064766	-0.341009	-0.516421	0.0358	0.0312	0.0016	nan	nan
2459508	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.613993	-0.474128	-1.111296	-0.639842	-0.676805	-0.526516	0.646224	0.500680	0.8941	0.9194	0.2214	0.000000	0.000000
2459505	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.164250	-0.018575	-0.427971	0.239079	0.396898	0.106152	0.822275	1.804857	0.8895	0.8489	0.2116	25.171787	17.252614
2459503	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.329442	-0.118349	-0.506414	-0.862563	0.353219	-0.067996	-0.019873	1.999363	0.8356	0.8241	0.5120	0.000000	0.000000
2459501	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.299032	-0.004276	-0.766411	-0.018024	0.121299	1.268773	-0.417662	1.081914	0.1223	0.1088	0.0140	0.000000	0.000000
2459500	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.652297	-0.089392	-0.847481	0.310393	-1.036889	-0.535541	-0.482795	0.126763	0.1435	0.1153	0.0148	0.000000	0.000000
2459499	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.620018	-0.471075	-1.108644	0.018010	-1.075722	-0.793202	-0.397779	2.738850	0.1230	0.1260	0.0091	0.000000	0.000000
2459498	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.060619	-0.165107	-0.892079	-0.300589	-0.718374	-0.933186	-0.240689	1.753555	0.1447	0.1106	0.0191	0.000000	0.000000
2459497	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.151645	-0.259086	-0.803574	-0.451157	-0.853742	-1.244196	-0.416660	2.086014	0.1329	0.1478	0.0240	0.000000	0.000000
2459496	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.124359	-0.331431	-0.868484	-0.394979	-0.796226	-1.162744	-0.317683	0.860482	0.1748	0.1238	0.0205	0.000000	0.000000
2459495	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	0.973883	-0.125917	-0.049169	-0.370087	0.556204	-1.028646	11.745474	1.745105	0.1582	0.1433	0.0233	0.000000	0.000000
2459494	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.290585	-0.088099	-1.003961	-0.018698	-1.170008	-1.026878	0.760826	2.525769	0.1553	0.1338	0.0226	0.000000	0.000000
2459492	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.604093	0.860874	-1.375601	-1.046560	0.082305	2.464153	-0.362338	-0.631670	0.7386	0.7929	0.3530	6.493385	5.022354
2459491	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.940223	1.547411	-0.933520	-0.041862	0.449861	0.963136	-0.681220	0.471372	0.7905	0.8136	0.2769	6.063293	3.446244
2459490	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	15.311416	0.844035	8.978048	-0.693350	14.243842	2.372402	75.352019	5.859756	0.6418	0.7896	0.4306	5.429247	5.089555
2459489	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.727391	1.218261	-1.553171	-0.512443	2.565710	3.441617	26.537398	3.479918	0.7547	0.8046	0.3238	10.229812	5.442335
2459488	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.510117	0.627230	-1.195590	-1.035769	-0.059570	1.053661	7.434680	-0.084680	0.7584	0.8072	0.3675	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 4 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 4, Node 1:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 4: 2459617

Antenna 4: 2459616

Antenna 4: 2459615

Antenna 4: 2459614

Antenna 4: 2459613

Antenna 4: 2459612

Antenna 4: 2459611

Antenna 4: 2459610

Antenna 4: 2459609

Antenna 4: 2459608

Antenna 4: 2459607

Antenna 4: 2459605

Antenna 4: 2459604

Antenna 4: 2459603

Antenna 4: 2459602

Antenna 4: 2459598

Antenna 4: 2459597

Antenna 4: 2459596

Antenna 4: 2459595

Antenna 4: 2459594

Antenna 4: 2459593

Antenna 4: 2459592

Antenna 4: 2459591

Antenna 4: 2459590

Antenna 4: 2459589

Antenna 4: 2459588

Antenna 4: 2459587

Antenna 4: 2459586

Antenna 4: 2459585

Antenna 4: 2459584

Antenna 4: 2459583

Antenna 4: 2459582

Antenna 4: 2459581

Antenna 4: 2459580

Antenna 4: 2459579

Antenna 4: 2459578

Antenna 4: 2459577

Antenna 4: 2459576

Antenna 4: 2459575

Antenna 4: 2459574

Antenna 4: 2459573

Antenna 4: 2459572

Antenna 4: 2459571

Antenna 4: 2459570

Antenna 4: 2459569

Antenna 4: 2459566

Antenna 4: 2459565

Antenna 4: 2459564

Antenna 4: 2459563

Antenna 4: 2459562

Antenna 4: 2459561

Antenna 4: 2459560

Antenna 4: 2459559

Antenna 4: 2459558

Antenna 4: 2459556

Antenna 4: 2459552

Antenna 4: 2459551

Antenna 4: 2459549

Antenna 4: 2459542

Antenna 4: 2459541

Antenna 4: 2459540

Antenna 4: 2459536

Antenna 4: 2459535

Antenna 4: 2459534

Antenna 4: 2459533

Antenna 4: 2459532

Antenna 4: 2459530

Antenna 4: 2459527

Antenna 4: 2459524

Antenna 4: 2459523

Antenna 4: 2459522

Antenna 4: 2459513

Antenna 4: 2459508

Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶